So my talk today is Computational Challenges in Space Research and my name
associated with. We'll see. I just want to
speak for a lot of like, like uh when
you see that, I just started like that because
that will happen with. Uh So here are the
topics that here are the topics that I'm going to
talk about a lot of uh probably less familiar with
what space sciences went into. My father in law
, people that he knows, he explains that I
have to go over and over again, not a
space. Um And I'll talk about some of the
activities within that space science Engineering research and figure I'll
describe some of the challenges of having a research program
that uh um day lining activities, uh the compression
algorithms, satellite, uh american simulations of the environment
and very uh I promised I would explain what space
sciences. So when my father in law business is
totally wrong because astrophysicists are interested in things that are
very, very far away black holes. And basically
out of space science is very much on the interaction
between the sun and the magnetic environment. Um So
when I tried to explain to my uh and I
said well why don't you think of me as an
enormous, I'm interested in just one. Uh huh
. So uh there are various realms some space some
some space scientists are interested in Seoul which uh some
uh some space scientists are interested in the magnetic field
magnetic environment here. And some space scientists are interested
in the apparatus. And this is more closely so
this this is actually a numerical simulation of the space
system. Uh This is called HD dynamic and fluid
stimulate combine that with the spokes fluid equations of Maxwell
magnetic equations. And it's showing every now and then
on CNN you will hear these reports that son did
something dramatic and it's gonna fall out. Well this
is what they're talking about, talking about a huge
explosion on the propagates through the solar system and then
hits the magnetic environment three days later field there.
And it produces these distortions that then produced electric fields
, electric currents that produced auroral displays, uh increased
drag on satellites and produced disruptions power on the ground
and computational challenge straight away because the numerical simulation is
trying to catch the details of the sun which is
on the lives and also catching simultaneously the details of
the response to that, which is on a much
smaller stations. So what you're seeing here in the
simulation is what's called active refinement, strong grade features
and uh refined men to capture the, So this
is what I'm going to show you what we do
have some uh uh the effects of the influence on
the environment sort of started an altitude of about 60
km in the atmosphere where the rapid sugar is chop
the islands and then magnetic fields go out into space
and pleasant environment. So all of this activity that
has its origins in the sun gets funneled down along
magnetic field lines and, and most of the influences
are felt close to the magnetic poles. When you
see the aurora systems electric fields which then coupled to
the upper atmosphere, which is ways uh regular,
regular structures and uh entitled uh, from a science
perspective, we're trying to understand cause and effective relationships
based system, but we're also try to mitigate some
uh problems that produce uh, society and some of
those. So this is what we call space weather
. Um, so something happens on CNN, uh
, uh, so charging banks on spacecraft regulations,
spacecraft, there can be damaged spacecraft, radiation damage
to uh, regular destruction, destruction, destruction to
satellite communications and navigation. Uh, the increased radiation
dosage people flying on airplanes go over the top of
the world. So, new york to uh,
Hong kong whole, so when they were in one
of the world's uh airplane, um there on the
ground. So the parents that are produced in the
ionosphere then induces parents in the ground and then leaked
into the power system. So transformers can get blown
up and they can be used disruptions, Hauer and
black out. Uh uh uh uh uh uh what
uh field? Uh All right. So, the
question is going to build anticipated in terms of trying
to understand the science of the coupling between the sun
, um solar wind, which is basically the outer
layer, just continually environment and atmosphere. The atmosphere
itself. We need spacecraft and spacecraft, uh,
get closer to the spacecraft in the atmosphere. So
, there is uh this is the problem that I
have the spacecraft and I do not directly the system
that I'm directly involved on the ground looking up space
. So basically has interests in ground based instruments and
satellite instruments, developing new instruments and then analyzing the
data from the instruments and also model and the environment
. So that's the world and tourist space. Look
at the past from the active, a little bit
more detail. So it's a lot. It was
incorporated as an official College of Engineering Research Center in
2007 and five years ago, probably seven years ago
is basically one of the planes. Um and now
as as you'll see with 13 faculty for faculty,
uh post graduate. So the scale of six or
seven years has grown to the extent that we are
now moving into a new building, which is uh
building that's been constructed in the corporate research. You
see uh 60 that's our new buildings were occupied the
grounds for that building were doing in late summer 2000
and 12 submission of space and B. T.
To provide forefront research construction and international average Space Time
21. And the engineering that allows you to explore
space utilizing a holistic approach of theoretical modeling and simulation
techniques, space design and experimental data acquisition do.
Um So for the rest of my four very quickly
constructed more about focused on research activities that we are
experiencing challenges to enter into the conversation. So these
are the these are the actors in space Bt right
now and the name on the left. So these
are just the faculty members, some of them are
teaching some of the research uh And then in the
sense that they're associated with and you can see that
there is a huge emphasis on the department we're trying
to broaden. All right uh right now, but
uh so right now our research activities broken down so
observations and development, building things and flowers, spacecraft
and ground based autonomous magnetic activity is focused around.
Um These these are showing uh one that I'm most
directly involved in the uh uh uh this place space
environment simulation modeling, uh space where the assimilation of
models, some of that is sitting right there.
Uh spacecraft modeling simulation and design. Uh So the
spacecraft instruments development uh uh these are some examples,
so uh Scott Haley was involved in the Nasa spacecraft
which was focused on understanding agronomy uh needlessly a layer
of the uh that's what's called a small explorer satellite
class uh is also involved in uh rocket experiments.
And Greg girl who recently joined the sea last year
is also involved in that uh and then what building
right now within space Bc. And is one of
the focuses uh presents computational challenge. Talk about later
in court is uh university class satellite water called.
Uh And these are little spacecraft still like this big
and I'll talk about what represents because they're small means
that computational uh that you have available small challenges there
. So that's a one slide overview of spacecraft stuff
. One slide overview of autonomous observatories. And this
is basically uh so there's a earlier on a lot
of the activity in the space environment is focused in
the whole regions poll and that's where it's cold in
there. So, uh there is a real need
to have uh measurements that can be uh collective year
round in a harsh environment autonomous uh flower is uh
involved in the project to design prototypes these instruments get
in places like Greenland, uh, magnetic measurements and
also GPS uh, receiver measurements that can be Uh
huh So this is what I'm involved in. And
I'll come back to this moment. Uh it's a
nature radar system, a system that works on similar
principles to the radars that you see at the end
of the news. Uh and I'll talk more about
this later. Uh in particular, we have a
similar technique for using multiple radar, uh, playing
scales, activities. So, he he has a
numerical model that allows him to model different uh phenomena
in space plasma, environment, turbulence, uh,
the effects of dust plasma. Uh, he also
has done some defense oriented work about modeling the effects
of a nuclear explosion in space. Um and again
, I'll come back to that later on. What
I'm doing here is I'm giving you a quick place
things I'll come back to later. Um And then
the space where the model, so uh simulations weighing
scales, a pure physics space sort of the equations
and I put them on an american and I run
them forward in time. There are also other classes
of models. There are playing statistical models are a
miracle. And then there are similar models where you
take a physics based model and you take data and
you can find the data with physics based model.
Uh use a forecast what they do when they're telling
you what the weather is going to be like a
basement. Now, it's guided by the data that
we have now, but also uh our understanding of
the uh how will propagate already based on and there's
a similar effort in the space environment uh monitoring uh
well, uh well, uh the computational challenge about
buying the data, uh so I'm going to present
four classes of challenges is and this is the one
that directly uh and what I'm going to present challenges
uh identified by name of people that are involved in
it. So depending if you are interested in that
, it's like, wow, expect what we're doing
, you can contact with relevant in this case.
Um This is a problem that we identify a number
of years ago and we thought there must be somebody
on campus and we move around on the locations in
your party as we over about three months and throughout
his labs showed what we do, he showed us
what he does and we sort of conversation going to
a point where we felt what a comeback. That's
fantastic. So what what what what was it that
motivated that's going on in the first place, was
the sheer volume of data that we have. Um
And this is this is this is common to a
lot of data looking activities that as uh as you
have instruments that are operating all the time data just
found and you just don't have the manpower to manually
extract information from. And people with a science background
, cure sort of physical science background. We have
certain skill set of data mining skills using uh techniques
but we had quickly, quickly but time realization that
we need the next uh So I'm talking to professor
around President. Uh we've educated ourselves on these ideas
of knowledge and uh techniques and uh months applying uh
techniques. Uh So this is this is uh still
a work in progress. But what is the data
that we're talking about? What we're talking about?
The super jewel radar network which is an international network
space where the radar uh accumulating data of a worldwide
migration involving uh more than a dozen countries and uh
academic and research institutions. Um and this is what
generates a signal and into the atmosphere. Um That's
what happens at HF frequencies. It was a higher
frequency the line, but it actually frequencies. And
this is what ham radio operator, radio operator on
the world. We use it in a radar.
So the single fans over. And then we're looking
for Sasha regular destructions alone, long magnetic. So
that allows us to get ridiculous of those uh structures
and maximize back. But some of the signals and
so far the ground and then some of them around
until we get some signals the refraction range of the
system. Thousands of so, three advantages of one
uh access to the irregularities that we really want to
see through. The refraction diffraction also extends the range
of 2000 and and also it operates continues uh All
right. Because it's a low power, relatively low
power. So these things run continuously and they like
gold, loads and loads of data and we just
were overwhelmed today. A data looks like this.
Um Uh the left is a scanned map showing philosophy
is measured by the radio during a two minute single
two minutes. And then if you imagine a slice
looking along a single direction, just accumulated a series
of what that what we saw in that one direction
as a function of time to get the pattern on
the flight on the right is showing the backs of
our development philosophy and development spectrum is a function of
time and there's a lot of features in here.
This is this is the essential problem is that I
can look at that and I can tell you a
lot of stuff that's going on in there just in
that 66 hours. There's a lot of things that
are going on in there that I would like to
analyze in the statistical sense, but it's just hard
features out that uh because this qualitative things going on
. Um and then we also produce the simulated maps
and then we can monitor get that map and we
can extract that time. So there's lots of lots
of love looking at this is, you know,
so on the panel and the top panel there,
uh that's just 1 25 these around the world and
their operating. So uh what this charge shows is
a hole based technologies that can attract uh the most
basic one is the velocity of those irregularities that tells
you what the electric field is and that, so
that's what we're known for. A lot of other
things that we can pull out people have references but
more more intensive. Okay. One of their radar
accumulate those on beam cell basis and it's just a
basic data product you put in a day, you
can get somebody else. Everything else underneath is a
larger scale phenomenon that has some space temporal character that
evolves in time. And so there's an element of
image processing associated with understanding. Um So there have
been proof of concept studies that say, yes,
we can examine the radar but there haven't been a
follow up statistical studies. Say how often we know
that we can see them in the data and playing
on any given day will look at our data and
obviously going through our data. But being able to
, you know, put a box around it and
pull out characteristics of wave number and the amplitude of
the fluctuation and these things that you really want to
get your hands around. Very difficult. Uh So
this is what we presented to Krishna and in particular
we focus and some explain this whole phenomenology uh help
us with it and said, well why don't we
just pick one? Let's try and focus on one
in the short term we think graduated and basically grabbing
. So what the other left there is showing uh
what's called uh line that is the single coming out
from the radar and then bouncing off coming out of
the ground. And the radar sends out signals over
a range of elevation angles and then it's reflecting on
the people have structures in it that produce these graduates
and those structures produced a focusing and focusing on the
ground. So then what's shown on the right here
is a time series showing the circle there. You
see that circle, there are strikes. And that
whole band of backscatter, there is the backscatter from
the ground, which is what cartoon show on there
. So the red. Alright, so where the
rays are coming together on the ground and the regions
where there are being used by the way. So
that show that this is what we're trying to find
out. Um He said, all right, I'll
help you with. I think I've already said.
So let's move on to what he looked at his
toolbox. He said, well, these are the
sorts of things that I do. He says,
I uh and like I said it three or four
months to sort of find the conversation with the same
language. So I'll take some of his surrogates.
I didn't know what that uh special aggregates, but
my understanding is the case. uh this is flo
happens and stitches them together and a picture of uh
uh this is a clustering stuff where he looks at
a diffused, then he does statistical uh analysis to
sort of figure out where the hot spots of activity
are. So in that context you would have to
mention the radar, the range in time and we
know what drill down and find. And then he
does this other thing called most mining uh the time
series analysis where he's looking for these interconnected triggers for
something and uh example uh chilling uh air conditioning units
or uh so we narrowed in on these. Well
he did so based on what you're showing, these
are the things that I think we can bring to
bear that I think might help you pull these things
out of your data more efficient. Uh and so
him in collaboration with the students came up with this
basic approach. So most mining temporal used to identify
a recurrent mostly with broadly similar but uh the problem
is for me is a physical scientists come up with
uh the or something but it's kind of you know
, anything that I come up with not nuanced and
sort of say well it looks like like this but
you know the buttons are identical. Is the thing
that I have uh complication he found was that the
most money generally applied time series rather than uh spatial
dimensions. Uh So he had to modify it and
uh huh So it doesn't work. Yeah. So
this is this is a time series of data.
So a time along the bottom and then range radar
along the and the strikes way passing through the atmosphere
producing focusing, focusing the that manifested in the data
is the stripes of strong backs and propagating. You
can see there's one this is, this is my
, I told me 1234567 89 10, 11,
12. It's like a dozen, at least a
dozen wave front. You can see there you're,
I can you can train computer to find out like
a, you know, you can train computer,
pick the dollar, then try and get the ones
, you know, false alarm rate. So as
I said, work in progress and this is what
it's doing right now, picking up the strong ones
. Um, but uh, so that's the first
computational challenge and we've already made connection on that.
Uh that's a work in progress uh for the rest
of the talk as much as I'm going to talk
about some of the challenges that we would like to
make new connections. Uh, The first one is
associated with huge standards. So where's the cubes cubes
out? Like I said, the beginning is a
spacecraft that looks like, right. Um It has
dimensions of 10 70 module and the idea is you
module arise the dimensions of these things and the basic
framework so that they can be popped in this launcher
then backs up on a rocket that's going up for
some other purpose and rocket a rocket or something like
that. So it's a leverage right on something that's
going up anyway. Um And it's perfectly all right
. And this is this is the direction of basic
B. C. Is going in. A very
aggressive action is to have a steady program development.
Uh um So we'll see you in many respects.
Uh But it has a problem in uh because everything
smaller computational power more and there are certain things that
satellite, there are basic things that satellite needs to
uh to function. It needs to have a good
knowledge of where it is and absorb it and where
it's pointing attitude control, where the critical functions.
Um and also the communication if you want to get
down from spacecraft, needs to know where it's pointing
down. Uh So over the years, the algorithms
, sophisticated algorithms have been developed or spacecraft attitude control
and telemetry. And when you try and put them
on that, uh you need to compress that algorithms
down because the computational power. Uh so this is
this is a pretty obvious and pressing challenge is experiencing
right now. How we press officially compress the algorithms
. So they used uh is an example of that
mission. Uh huh. Yeah. Oh, okay
. A proposal. So this is this is a
proposal for a mission called lace which is looking at
the lower atmosphere and experiment goals identified there. But
parts that are drawing attention to here is the environment
, but it's got some, you know, some
numbers on that. Uh This is our process uh
size about memory, uh modulation scheme that we use
here is the data requirements data down on a daily
basis to the commission. Um and then we've got
a ground station and and then the last one,
this is the challenge we need on board a bit
. This is a piece that we're kind of still
working a similar problem with calling space. So the
idea here is that launch a rocket, you want
to understand the atmosphere properties of the atmosphere. You
launch a rocket and has this instrument on it basically
is field some instruments inside the sphere drops through the
atmosphere from the rocket. You get information about the
atmosphere, but again, you didn't have a good
idea of how the tunnels. Yeah. So you
need to have on the fly sort of uh,
we've taken the measurements and it's looking in this direction
. But again, it's a very small object and
everything is compressed computing power. And so this is
uh, mm hmm. Uh, this one I
will, this is troy innocence. Like I think
the basic idea is that you launched the spacecraft into
a parking lot. And then over time you make
use of the motivations in the natural environment to spread
its constellation out the passage of time. And uh
, uh, constellation could sort of broad coverage.
And I think the challenge here is to understand the
real patients, uh, an efficient way. I
think there's a lot of iterations associated solving the equation
to properly specify how you get from this way it's
going to be. Um, and then this is
uh published on the tube sets that have antennas trying
to communicate the ground and make sense of trying to
uh data from different directions of the space environment you
need to have after uh attitude, uh reference to
these three. Access your access the role, access
and access. It tends to have more measurements,
knows uh it made all the processing star senses,
uh uh uh required uh process uh uh job that
larger spacecraft uh talk about uh uh propagation uh uh
uh process environment with uh uh uh he has a
small sort of rolls up into a larger um turbulence
structure uh for instance, uh and they understand the
impact of technology such as communication and navigation system.
And then the exploitation of these speeches for understanding the
wire uh environment uh in particular. So this is
, well, this is the great, so there's
a continuity equation uh which is sort of uh changes
, uh time, uh source gradients and uh for
electron islands. And then uh huh talk to me
and then this one time saying is more high Maxwell
, I think. Um so the way America Britain
and uh and that applies these uh simulations to specific
. So uh emphasis on closing the loop. So
you have a model, you simulate the environment and
then you compare the data model, makes predictions.
So, uh scales had a trip to uh facility
in Alaska and this is uh goes up into the
air and it excites the irregular structures in the United
States. And in that way, which then uh
being picked up by a so by modeling the response
to the here and then comparing with data. You
can see that he was working on a uh and
what does the what does that tell you about what's
going on in that region? So this is this
is an example of that. So on the left
is a a spectrum of electromagnetic region, and then
on the right is a simulation of what they expect
and uh but a challenge in the simulations. So
if he wants to simulate, you know, radar
experiment that took a few hours a month, so
his challenges more realistic. So first correspondence, he
wants to push it further right now. Take a
month to run just one simple experiment. So he
needs to parallel lives uh and really push it higher
uh computational. So you look at the collaborators on
that. Uh So that's that's heating heating the atmosphere
and looking at the response of the atmosphere and simulated
. Uh also does work with uh The idea here
is if you launch a rocket, uh has dust
trail associated and then measure the uh uh uh and
then using ground regular again to measure the time.
Uh and then uh so this simulation uh particular arrangement
of uh electric fields and magnetic fields and small uh
regular structures, given the characteristics of the arrangement of
these various things can roll up into this. Uh
huh. But again, uh it's computational intensive,
need parallel. Uh Okay, so the last one
uh actually uh so uh All right, so this
is atmospheric modeling simulation three and like a touched on
this earlier. So the idea is that um so
we have measurements of the space environment and we have
a business based understanding of how the uh system evolves
in science. Can we combine the measurements with based
model? Um Come up with what looks like right
now and they're already in the short term forecast,
which is exactly the same thing they do with uh
dot com. Uh but problems in the space environment
. So, weather weather dot com has the advantage
that they have measurements all over the place. They
take measurements twice a day at the airport and take
measurements that they use to nudge the physics based model
of the atmosphere in the right direction. Right.
Uh Space environment, we have two problems uh in
contrast to that one, we don't have the distribution
of measurements that normal weather forecast. And the second
is that the space environment is more strongly force than
the the atmosphere actually has. A lot of them
. All right. And it's pretty simple, you
know, driven by sunlight, which is fairly uniform
and it has its inertia. And so uh physics
based model that is more forward in time is actually
fairly, it's fairly smooth space environment, It is
a lot more chaotic. A small swing in one
parameter can produce huge because the electromagnetic coupling so strong
. So we have a problem with lack of data
coverage and the fact that it's a highly for system
, which means that assimilating data model is much more
of a challenge. Um and this is an active
area of research um and in particular life simulation uh
require uh significant computational together. Uh um uh this
is yeah, so everybody has a different function uh
actually uh another monitor double shield. And this is
a lot of the database and driving into the blood
system. Yeah, so again, it's trying to
conversational push parallelization or more elegant. Find him.
Yeah. All right. That's the end of my
talk. Um so this is a summary, hopefully
what you have uh when somebody asks you what's the
difference between an astro space scientists uh uh also uh
around standing and basically uh huh And then computational challenges
that uh characterized the line between uh no known features
and as yet unknown. Uh and then the need
for professional applications for uh attitude control and telemetry and
uh uh numerical simulations, space latin environment, the
physics, So there's a model that exists and it
seems to be able to capture first daughter effects and
turbulence and needing experiments, but in order to push
it to high levels of nuance, doesn't need parallelized
it and uh impressive efficiency. And then the last
one extract welding assimilation problems, uh getting state.
Uh so subjects collaboration as well. So if you've
seen anything here that is of interest to you or
your students professor isn't. Uh huh. Well,
thank you. Thank you. Okay.